An improved ant colony optimization algorithm based on context for tourism route planning

Liang, Shengbin; Jiao, Tongtong; Du, Wencai; Qu, Shenming

doi:10.1371/journal.pone.0257317

Cited by 31 publications

(25 citation statements)

References 29 publications

(28 reference statements)

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“…Brachman and Anand (1996) give a very practical view to emphasize the interactive nature of the data mining process. Here, we can summarize the following basic steps [6]:…”

Section: Related Workmentioning

confidence: 99%

Design and Application of Multiattribute Tourist Information Recommendation Model Based on User Interest

Lian

Liang

2022

Wireless Communications and Mobile Computing

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There exist various challenges introduced by a large number of multimedia photos and videos for personalized travel recommendation in the era of big data. In order to resolve such challenges, a context-aware personalized travel recommendation system based on data mining is proposed in this study. It is a framework that can locate and summarize travel locations based on a user-given collection of geotagged photos and build up each user’s travel history to obtain their travel preferences, so as to perform contextual multiattribute personalized queries, thereby recommending travel locations that best suit their interests. The primary objective is to lay the foundation for developing personalized travel solutions and help the transformation and upgrading of the tourism industry. Thus, this paper proposes a design and application of a multiattribute travel information recommendation model based on user interests for the contradiction between the personalized travel demand of tourists and traditional travel methods. It analyzes the designed travel transportation network and builds a prototype system for travel recommendation by mining a large number of scenic spot information datasets. In association to this, an advanced recommendation algorithm is also designed. The experimental results reveal the fact that by integrating various attributes, the comprehensive evaluation mechanism of scenic spots is capable of providing enhanced reasonable and comprehensive evaluation of scenic spots, which lays the foundation for subsequent route recommendation. Secondly, in comparison to the existing path recommendation algorithms, the recommendation algorithm proposed in this paper has the potential to meet various constraints and goals of the users and recommend routes that have better reasonableness and diversity. Also, this algorithm has low complexity in terms of running time which acts as an added advantage.

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“…Brachman and Anand (1996) give a very practical view to emphasize the interactive nature of the data mining process. Here, we can summarize the following basic steps [6]:…”

Section: Related Workmentioning

confidence: 99%

Design and Application of Multiattribute Tourist Information Recommendation Model Based on User Interest

Lian

Liang

2022

Wireless Communications and Mobile Computing

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“…In recent years, scholars (both in China and abroad) have extensively researched the optimization of tourist routes, and have proposed many research methods. The research methods involved have made use of various algorithms such as the ant colony algorithm [8,9], genetic algorithm [9], degenerate algorithm [10], probability prediction algorithm [11], data mining [12], backtracking algorithm [3] and so on. Such as optimization of tourist routes based on tourists, Wei Sun used the ant colony algorithm and the cluster analysis to build a model with the shortest time, lowest cost, and best travel experience to study the national 5Alevel tourist routes [13].…”

Section: Introductionmentioning

confidence: 99%

“…The main goal is to develop tourism as a pillar industry, and promote the development of surrounding industries with tourism industry at the center. On the regional scale, scenic spots in Songshan Scenic Area [25], Lushan Scenic Area [26], Gulangyu Scenic Area [27], World Expo Garden Scenic Area [28], forest wetland [9], and other sites have been investigated. The design of tourism routes in these scenic areas has focused on self-driving tours, scientific investigation tours, and other activities.…”

Section: Introductionmentioning

confidence: 99%

Optimization of tourism routes in Lushunkou District based on ArcGIS

Pei

Wang

et al. 2022

PLoS ONE

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With the advancements and developments in China’s tourism industry, various autonomous forms of tourism have been gaining prominence. As such, to facilitate tourists and provide them with maximum experience while economizing on time and cost is essential. One approach toward achieving this is the optimization of tourism routes. However, so far the studies on this approach have focused primarily on inland tourist sites and have lacked a geographic perspective. Therefore, this study undertook the tourism resource data of Lushunkou District of 2020, used the ArcGIS accessibility evaluation model to analyze tourism resources, and finally used the Vehicle Routing Problem of network analysis technology to optimize the tourism route of Lushunkou District and obtain the general overall intellectual framework and technical methods for tourism route optimization. The results showed that the ArcGIS accessibility evaluation model could be used to integrate resources in the tourism area before using the Vehicle Routing Problem to optimize the analysis of tourism routes, thereby enabling the separation of different types of tourism. These divisions were based on the Vehicle Routing Problem to optimize routes for one-day and two-day tours. A new method and model for optimization for tourism routes was constructed to provide a basis and reference for the optimization of tourism routes in similar cities. The observations and results of the present study can facilitate the government in developing the tourism industry and maximizing the benefits obtained from them. Further, travel agencies and tourists will have the provision of designing optimum tourism routes.

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“…Among these methods, PSO is famous for fast convergence and easy applying. PSO algorithms are widely applied in engineering like route planning [ 8 , 9 ], data clustering [ 10 , 11 ], feature selection [ 12 , 13 ], image segmentation [ 14 , 15 ], power system [ 16 , 17 ], engineering areas [ 18 – 20 ], and so on.…”

Section: Introductionmentioning

confidence: 99%

An electronic transition-based bare bones particle swarm optimization algorithm for high dimensional optimization problems

et al. 2022

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An electronic transition-based bare bones particle swarm optimization (ETBBPSO) algorithm is proposed in this paper. The ETBBPSO is designed to present high precision results for high dimensional single-objective optimization problems. Particles in the ETBBPSO are divided into different orbits. A transition operator is proposed to enhance the global search ability of ETBBPSO. The transition behavior of particles gives the swarm more chance to escape from local minimums. In addition, an orbit merge operator is proposed in this paper. An orbit with low search ability will be merged by an orbit with high search ability. Extensive experiments with CEC2014 and CEC2020 are evaluated with ETBBPSO. Four famous population-based algorithms are also selected in the control group. Experimental results prove that ETBBPSO can present high precision results for high dimensional single-objective optimization problems.

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An improved ant colony optimization algorithm based on context for tourism route planning

Cited by 31 publications

References 29 publications

Design and Application of Multiattribute Tourist Information Recommendation Model Based on User Interest

Design and Application of Multiattribute Tourist Information Recommendation Model Based on User Interest

Optimization of tourism routes in Lushunkou District based on ArcGIS

An electronic transition-based bare bones particle swarm optimization algorithm for high dimensional optimization problems

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